fix(compaction): fall back to reasoning text when the summary has none

A reasoning model can spend the whole summary output budget thinking and return only a reasoning item. _extract_text read only output messages, so compaction logged 'summary returned no content' and the agent failed. Use the reasoning text, with a warning, when there is no output text.

strix/llm/compaction.py

@@ -15,7 +15,11 @@ from typing import TYPE_CHECKING, Any
 
 from agents.model_settings import ModelSettings
 from agents.models.interface import ModelTracing
-from openai.types.responses import ResponseOutputMessage, ResponseOutputText
+from openai.types.responses import (
+    ResponseOutputMessage,
+    ResponseOutputText,
+    ResponseReasoningItem,
+)
 
 from strix.config import load_settings
 from strix.config.models import StrixProvider
@@ -288,15 +292,22 @@ def _checkpoint_item(summary: str) -> dict[str, Any]:
 
 def _extract_text(response: ModelResponse) -> str:
     parts: list[str] = []
+    reasoning: list[str] = []
     for item in response.output:
-        if not isinstance(item, ResponseOutputMessage):
-            continue
-        parts.extend(
-            chunk.text
-            for chunk in item.content
-            if isinstance(chunk, ResponseOutputText) and chunk.text
-        )
-    return "".join(parts)
+        if isinstance(item, ResponseOutputMessage):
+            parts.extend(
+                chunk.text
+                for chunk in item.content
+                if isinstance(chunk, ResponseOutputText) and chunk.text
+            )
+        elif isinstance(item, ResponseReasoningItem):
+            reasoning.extend(summary.text for summary in item.summary if summary.text)
+    if parts or not reasoning:
+        return "".join(parts)
+    # Reasoning models can spend the whole output budget thinking and return no
+    # message; their reasoning is a degraded but usable summary.
+    logger.warning("compaction summary had no output text; using reasoning text")
+    return "\n".join(reasoning)
 
 
 async def _summarize(model: str, prompt: str, max_tokens: int) -> str | None:

tests/test_compaction.py

@@ -6,6 +6,8 @@ from types import SimpleNamespace
 from typing import TYPE_CHECKING, Any
 
 import pytest
+from agents.extensions.models.litellm_model import InternalChatCompletionMessage
+from agents.models.chatcmpl_converter import Converter
 from litellm.exceptions import BadRequestError, ContextWindowExceededError, RateLimitError
 from openai.types.responses import ResponseOutputMessage, ResponseOutputText
 
@@ -242,6 +244,30 @@ async def test_summarize_routes_through_provider_with_settings(
     assert settings.max_tokens == 64
 
 
+@pytest.mark.asyncio
+async def test_summarize_falls_back_to_reasoning_when_no_output_text(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    # A reasoning model that spends its budget thinking returns only a reasoning item.
+    _patch_budget(monkeypatch, keep_tokens=30, window=4_000)
+    message = InternalChatCompletionMessage(
+        role="assistant", content=None, reasoning_content="REASONED SUMMARY"
+    )
+    response = SimpleNamespace(output=Converter.message_to_output_items(message))
+
+    class FakeModel:
+        async def get_response(self, **_kwargs: Any) -> Any:
+            return response
+
+    class FakeProvider:
+        def get_model(self, _model_name: str | None) -> Any:
+            return FakeModel()
+
+    monkeypatch.setattr(compaction, "StrixProvider", FakeProvider)
+
+    assert await compaction._summarize("m", "p", 64) == "REASONED SUMMARY"
+
+
 def test_fit_to_tokens_truncates_oversized_text(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.setattr(compaction, "count_tokens", lambda _m, t: len(t))
     text = "x" * 10_000